File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A holonic approach to flexible flow shop scheduling under stochastic processing times

TitleA holonic approach to flexible flow shop scheduling under stochastic processing times
Authors
Issue Date2014
PublisherElsevier.
Citation
Computers and Operations Research, 2014, v. 43, p. 157–168 How to Cite?
AbstractFlexible flow shop scheduling problems are NP-hard and tend to become more complex when stochastic uncertainties are taken into consideration. This paper presents a novel decomposition-based holonic approach (DBHA) for minimising the makespan of a flexible flow shop (FFS) with stochastic processing times. The proposed DBHA employs autonomous and cooperative holons to construct solutions. When jobs are released to an FFS, the machines of the FFS are firstly grouped by a neighbouring K-means clustering algorithm into an appropriate number of cluster holons, based on their stochastic nature. A scheduling policy, determined by the back propagation networks (BPNs), is then assigned to each cluster holon for schedule generation. For cluster holons of a low stochastic nature, the Genetic Algorithm Control (GAC) is adopted to generate local schedules in a centralised manner; on the other hand, for cluster holons of a high stochastic nature, the Shortest Processing Time Based Contract Net Protocol (SPT-CNP) is applied to conduct negotiations for scheduling in a decentralised manner. The combination of these two scheduling policies enables the DBHA to achieve globally good solutions, with considerable adaptability in dynamic environments. Computation results indicate that the DBHA outperforms either GAC or SPT-CNP alone for FFS scheduling with stochastic processing times.
Persistent Identifierhttp://hdl.handle.net/10722/198488
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWANG, Ken_US
dc.contributor.authorChoi, SHen_US
dc.date.accessioned2014-07-07T07:12:49Z-
dc.date.available2014-07-07T07:12:49Z-
dc.date.issued2014en_US
dc.identifier.citationComputers and Operations Research, 2014, v. 43, p. 157–168en_US
dc.identifier.urihttp://hdl.handle.net/10722/198488-
dc.description.abstractFlexible flow shop scheduling problems are NP-hard and tend to become more complex when stochastic uncertainties are taken into consideration. This paper presents a novel decomposition-based holonic approach (DBHA) for minimising the makespan of a flexible flow shop (FFS) with stochastic processing times. The proposed DBHA employs autonomous and cooperative holons to construct solutions. When jobs are released to an FFS, the machines of the FFS are firstly grouped by a neighbouring K-means clustering algorithm into an appropriate number of cluster holons, based on their stochastic nature. A scheduling policy, determined by the back propagation networks (BPNs), is then assigned to each cluster holon for schedule generation. For cluster holons of a low stochastic nature, the Genetic Algorithm Control (GAC) is adopted to generate local schedules in a centralised manner; on the other hand, for cluster holons of a high stochastic nature, the Shortest Processing Time Based Contract Net Protocol (SPT-CNP) is applied to conduct negotiations for scheduling in a decentralised manner. The combination of these two scheduling policies enables the DBHA to achieve globally good solutions, with considerable adaptability in dynamic environments. Computation results indicate that the DBHA outperforms either GAC or SPT-CNP alone for FFS scheduling with stochastic processing times.en_US
dc.languageengen_US
dc.publisherElsevier.en_US
dc.relation.ispartofComputers and Operations Researchen_US
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in <Journal title>. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in PUBLICATION, [VOL#, ISSUE#, (DATE)] DOI#en_US
dc.titleA holonic approach to flexible flow shop scheduling under stochastic processing timesen_US
dc.typeArticleen_US
dc.identifier.emailChoi, SH: shchoi@hkucc.hku.hken_US
dc.identifier.authorityChoi, SH=rp00109en_US
dc.identifier.doi10.1016/j.cor.2013.09.013en_US
dc.identifier.hkuros229955en_US
dc.identifier.volume43en_US
dc.identifier.spage157–168en_US
dc.identifier.epage157–168en_US
dc.identifier.isiWOS:000329383300015-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats